v0.2.7

This version adjusts the default parameter bounding for fitting peak amplitudes and widths. It also adds in a new check to make sure the approximate_peak_width is reasonable given the sampling frequency of the data. Additionally, type hints are added to the hplc.quant module to aid development.

0.2.6

What's Changed

• A new statistic signal_maximum is returned when fit_peaks() is called. This corresponds to the maximum signal observed in a peak reconstruction.

Full Changelog: 0.2.5...0.2.6

0.2.5

Full Changelog: 0.2.4...0.2.5

0.2.4.post1

What's Changed

• Add dependencies to setup.py by @florian-huber in #13

New Contributors

• @florian-huber made their first contribution in #13

Full Changelog: 0.2.3...0.2.4.post1

0.2.4

What's Changed

• Add dependencies to setup.py by @florian-huber in #13

New Contributors

• @florian-huber made their first contribution in #13

Full Changelog: 0.2.3...0.2.4

0.2.3

What's Changed

• Bug fix for: #10 small issue in correct baseline method by @gchure in #11

Full Changelog: v0.2.2...0.2.3

0.2.2

This release fixes a bug in global parameter bounding and adds a test coverage. It also includes modifications to the documentation including the addition of a new tutorial that demonstrates how to use hplc-py to generate a calibration curve.

0.2.10

This release of hplc-py fixes several small bugs discovered in further testing and validation. The major bug fix was the addition to standardize the time window over which peak areas can be integrated, which is necessary when using calibration curves to quantify data within chromatograms. This has been included as a new keyword argument integration_window in the .fit_peaks() method of a Chromatogram object.

Further unit testing of the io.load_chromatogram() function has now been implemented and the scope of this function has been reduced to accept only one chromatogram object at a time.

0.2.0

This release includes new features for manually positioning known peaks, modifying individual peak parameters, accounting for negative peak integration, and renaming some variables for internal consistency.

Cut of beta release, v.0.1.1

This is the first official release of hplc-py with a version 0.1.0! This is a stable release that has a tested suite of functions for quantifying chromatography data. While not a pre-release, this release will soon be updated given use feedback by collaborators and in preparation for formal publication.

This release supersedes v0.1.0.post1.